2 resultados para Fuzzy semi inner products,

em Aston University Research Archive


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One dominant feature of the modern manufacturing chains is the movement of goods. Manufacturing companies would remain an unprofitable investment if the supplies/logistics of raw materials, semi-finished products or final goods are not handled in an effective way. Both levels of a modern manufacturing chain-actual production and logistics-are characterized by continuous data creation at a much faster rate than they can be meaningfully analyzed and acted upon manually. Often, instant and reliable decisions need to be taken based on huge, previously inconceivable amounts of heterogeneous, contradictory or incomplete data. The paper will highlight aspects of information flows related to business process data visibility and observability in modern manufacturing networks. An information management platform developed in the framework of the EU FP7 project ADVANCE will be presented.

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In order to survive in the increasingly customer-oriented marketplace, continuous quality improvement marks the fastest growing quality organization’s success. In recent years, attention has been focused on intelligent systems which have shown great promise in supporting quality control. However, only a small number of the currently used systems are reported to be operating effectively because they are designed to maintain a quality level within the specified process, rather than to focus on cooperation within the production workflow. This paper proposes an intelligent system with a newly designed algorithm and the universal process data exchange standard to overcome the challenges of demanding customers who seek high-quality and low-cost products. The intelligent quality management system is equipped with the ‘‘distributed process mining” feature to provide all levels of employees with the ability to understand the relationships between processes, especially when any aspect of the process is going to degrade or fail. An example of generalized fuzzy association rules are applied in manufacturing sector to demonstrate how the proposed iterative process mining algorithm finds the relationships between distributed process parameters and the presence of quality problems.